Survival Prediction

Survival prediction aims to forecast the time until a specific event, such as death or disease progression, using patient data. Current research heavily utilizes deep learning, employing architectures like transformers, convolutional neural networks, and autoencoders, often incorporating multimodal data (e.g., medical images, genomics, clinical records) to improve prediction accuracy. This field is crucial for personalized medicine, enabling more informed treatment decisions and risk stratification for patients across various diseases, particularly cancers, and improving overall healthcare outcomes.